Associative and Parallel Processors
ACM Computing Surveys (CSUR)
Experimental Construction of Very Large Scale DNA Databases with Associative Search Capability
DNA 7 Revised Papers from the 7th International Workshop on DNA-Based Computers: DNA Computing
Graphs and Hypergraphs
A bayesian algorithm for in vitro molecular evolution of pattern classifiers
DNA'04 Proceedings of the 10th international conference on DNA computing
Evolutionary hypernetwork models for aptamer-based cardiovascular disease diagnosis
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Evolutionary hypernetwork classifiers for protein-proteininteraction sentence filtering
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Evolutionary hypernetworks for learning to generate music from examples
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
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Content-addressability is a fundamental feature of human memory underlying many associative information retrieval tasks. In contrast to location-based memory devices, content-addressable memories require complex interactions between memory elements, which makes conventional computation paradigms difficult. Here we present a molecular computational model of content-addressable information storage and retrieval which makes use of the massive interaction capability of DNA molecules in a reaction chamber. This model is based on the “hypernetwork” architecture which is an undirected hypergraph of weighted edges. We describe the theoretical basis of the hypernetwork model of associative memory and its realization in DNA-based computing. A molecular algorithm is derived for automatic storage of data into the hypernetwork, and its performance is examined on an image data set. In particular, we study the effect of the hyperedge cardinality and error tolerance on the associative recall performance. Our simulation results demonstrate that short DNA strands in a vast number can be effective in some pattern information processing tasks whose implementation is within reach of current DNA nanotechnology.